bridge pier scourr: a revieww of processess

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Environmental Engineering and Management Journal May 2012, Vol.11, No. 5, 975-989http://omicron.ch.tuiasi.ro/EEMJ/

“Gheorghe Asachi” Technical University of Iasi, Romania

BRIDGE PIER SCOUR: A REVIEW OF PROCESSES,

MEASUREMENTS AND ESTIMATES

Luigia Brandimarte

, Paolo Paron, Giuliano Di Baldassarre

UNESCO-IHE, Institute for Water Education, Westvest 7, 2601 DA Delft, The Netherlands

Abstract

Scouring of piers and abutment has been recognized as the main cause of damage and failure of bridges over waterways. Thescientific community has produced a number of studies addressing the complex characteristics of the scour process and has provided engineers with several techniques for the estimate of the maximum expected scour depth at a bridge site. Nevertheless,the prediction of scour depths is affected by many sources of uncertainty, such as observation uncertainty, parameter uncertainty,and structural uncertainty. Only a few studies have recently tried to estimate the uncertainty associated to the scour depth prediction.This paper offers a broad review of the main aspects to be taken into account when analyzing bridge pier scour: 1) processes: to better understand the dynamics triggering pier scour, an analysis of the type of scour occurring at bridge piers, the most

influencing factors, failure mechanisms and local pier scour dynamics is carried out; 2) measurements: one of the main difficultiesfaced in the real world practice is scour data collection; this session reviews the latest techniques available for the measurementsof the scour depth at bridge piers; 3) estimates: this session critically reviews different approaches the scientific literature hasoffered for the estimate of the maximum local scour depth and discusses the difficulty to address uncertainty in the estimates.This review is meant to be a useful reference for scientists and technicians dealing with the bridge pier scour issue.

Key words: bridge failure, pier scour, scour dynamics, scour measurements, scour estimates

Received: October, 2011; Revised final: April, 2011; Accepted: May, 2011

Author to whom all correspondence should be addressed: e-mail: [email protected]; Phone:+31 15 215 1869; Fax:+31 15 212 29 21

1. Introduction

Bridges have always been a big challenge for

engineers and builders, both in their design stage andin maintaining their stability and function over time.Indeed, for the Ancient Romans, these fascinatingarchitectural structures that allowed man to overcamenatural impediments were considered not just atechnical and engineering masterpiece but, because ofthe huge effort that it took to erect them, also a sort of“architectural miracle” (Brandimarte and Woldeyes,2012).

Furthermore, the engineers who built themwere considered a type of High Priest (the wordPontifex comes from the Latin Pontem Facere thatmeans “to build bridges”), acting as mediators

between Gods and the believers.

Any kind of structure in river channels inducesa forced interaction between the structure itself andthe natural river flow.

Quite generally, a crossing bridge, with pierand abutments in the river bed and banks, representsan alteration of the natural geometry of the riversection and, thereby, creates an obstacle for the riverflow that, as it approaches the bridge, has to changeits own natural pattern; furthermore, because of themodified flow conditions at the bridge crossing, thestreamflow acquires a strong erosive power.

As a consequence, in the subcritical flowconditions that are usually encountered in riverchannels, the resulting increase in flow velocity anderosive power of the streamflow creates conditionsthat endangers the stability of bridge foundations.


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Brandimarte et al./Environmental Engineering and Management Journal 11 (2012), 5, 975-989

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An interesting and valuable document by TitusLivius represents one of the most ancient evidence ofthe interaction between water and bridges: the Romanhistorian recorded that in 193 B.C. a flood destroyedtwo wood bridges over river Tiber, in Rome. Otherfloods occurred and, as a direct consequence, thecensors Marcus Aemilius Lepidus and Marcus

Fulvius Nobilior were asked to build the first bridgein stone in Rome (Bersani and Bencivenga, 2001;Segarra Lagunes, 2004).

The story of this unfortunate bridge that proved to be extremely sensitive to the scouring effectof the flowing water is characterized by a series ofinterventions that were designed to stabilize thestructure after being damaged by several flood events(Bersani and Bencivenga, 2001). The lastreconstruction lasted only 23 years because onDecember 24th 1598 three of the six arches of the

bridge were destroyed by an extraordinary flood ofTiber River and since then the bridge got the name of

“Ponte Rotto” (Broken Bridge). Only one of the sixoriginal arches of the bridge is still standing andPonte Rotto is now an attractive roman ruin fortourists and a token of bridge scouring fortechnicians.

This tragic story of the “Ponte Rotto” bridge isnot a statement of the incompetence of Romanengineers. Indeed, even now in modern times, pierand abutment undermining due to scouring andriverbed erosion has been widely recognized as beingthe main cause for bridge damage and failure(Melville and Coleman, 2000; Richardson and Davis,2001). According to a comprehensive collection of

bridge failure data worldwide gathered by Imhof(2004), natural hazard is the main cause of bridgecollapse (Fig. 1) and among the natural hazard listedcauses, flooding or scour is responsible worldwide foraround 60% of the collapses (Fig. 2).

0 10 20 30 40

1

% Total collected bridge collapses

C a u s e s o f c o l l a p s e natural hazard

design error

impact

overloading

human error

limited knowledge

deterioration

vandalism

Fig.1. Main causes of bridge collapse (Imhof, 2004)

The Federal Highway Administration (FHWA)has estimated that 60% of bridge collapses in the

USA is due to scour (FHWA, 1988; Parola et al.,1997) and, on average, about 50 to 60 bridges faileach year in the USA (Shirhole and Holt, 1991).

Wardhana and Hadipriono (2003) studied 500failures of bridge structures in the United States

between 1989 and 2000 and showed that the mostrecurrent causes of bridge failures were due to floods,scour and impacts. The average age of the 500 failed

bridges was 52.5 years, ranging from 1 year to 157years.

0 20 40 60 80

1

% Total collected bridge collapses

N a t u r a l h a z a r d s

storm

explosion

earthquake

flloding/scour

Fig.2. Different natural hazards causing bridge collapse (Imhof, 2004)

These effects of bridge scour are profound.Bridge damage and failure have deep social andeconomic implications due to the costs ofreconstruction, maintenance and monitoring ofexisting structures, the disruptions of trafficcirculation and, in some extreme cases, the cost ofhuman lives. In a wide research on bridge scour, the

Federal Highway Administration (Brice and Blodgett,1978) reported that damages to bridges and highwaysfrom major regional floods in 1964 and 1972amounted to about US$100 million per event; in NewZealand a survey of roading authorities showed thatscour caused by rivers results in roading expenditureof NZ$36 million per year (Macky, 1990).

The survey also showed that the expenditureson scour-related bridge damage amounted to about

NZ$18 million per year, with more than 70% of theseexpenditures being related to bridge repairs ratherthan preservative maintenance or construction of new(replacement) bridges (Melville and Coleman, 2000).

Although the dynamic of bridge scouring iswell known and several studies are available in theliterature for interpreting the scour process and

predicting the maximum scour depth (Graf, 1998;Melville and Coleman, 2000), over the past decades anumber of bridge damages that occurred during riverfloods has shaken the scientific community andspurred engineers and researchers to improve scour

prediction models and to renew scour measurementtechniques. Indeed, by looking at the databasecollected by Imhof (2004), one can notice that the

percentage of collapsed bridge has increased in the past decades (Table 1): while collapses due to limitedknowledge or design error have decreased in time,those due to natural hazards have increased.


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Bridge pier scour: A review of processes, measurements and estimates

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This might be due to the aging of the structuresand lack of maintenance, changes in the impact ofhydrological conditions due to changes in thecharacteristics of the river basin.

This review covers three of the main aspects to be taken into account when analyzing bridge pierscour: 1) processes: to better understand the dynamics

triggering pier scour, an analysis of the type of scouroccurring at bridge piers, the most influencing factors,failure mechanisms and local pier scour dynamics iscarried out; 2) measurements: one of the maindifficulties faced in the real world practice is scourdata collection; this session reviews the latesttechniques available for the measurements of thescour depth at bridge piers; 3) estimates: this sessioncritically reviews different approaches the scientificliterature has offered for the estimate of the maximumlocal scour depth and discusses the difficulty toaddress uncertainty in the estimates.

This review is meant to be a useful reference

for scientists and technicians dealing with the bridge pier scour issue. It is worth mentioning that scour athydraulic structures is an important process that altersthe sediment-flow equilibrium and thus haveconsequences on the ecosystems at the cross sectionscale, flood vulnerability in the vicinity of thestructure and alteration of local geomorphologiccharacteristics. It is important, then, that scientistslook at processes and estimates of scour depthevolution at structures in order to predict theirenvironmental effects on the local scale.

2. Processes

2.1. Type of bridge scour

Scour at bridge crossings is the result of theerosive action of flowing water, when it has thestrength to excavate and carry away material fromaround bridge piers and bridge abutments(Richardson and Davis, 2001). Scour depth is thelowering of the river bed level and is a measure of thetendency to expose bridge foundations (Melville andColeman, 2000). Although scour process mechanismsare well established, quantifying the magnitude ofscour at bridge crossing is not an easy task, due not

only to the complexity of the cyclic nature of the phenomenon, but also to the fact that bridge

geometry, river channel morphology and hydrologicregime are different for each bridge.

Scour at bridge crossings is usually the resultof the joint effects of three different scour processes(general scour, contraction scour and local scour at

piers and abutments) (Fig. 3) that may occur eitherindependently or simultaneously, whose different

origin suggests a different estimate of each individualscour contribution.

Fig.3. Sketch of the type of scour that can occur at a bridgecrossing

A channel with a mobile bed is usuallyexposed to a General Scour, which takes placeindependently of the presence of the bridge and is dueto streambed elevation changes in the reach where the

bridge is located.The main causes of general scour that induce

aggradation or degradation of the bed channel are

either due to natural phenomena, such as channelstraightening, climate changes and land activities(landslides, mudflows) or to human activities, such asland-use changes (deforestation, urbanisation), damand reservoir construction, river bed material miningand channel alterations.

In the presence of bridge crossings, additionalscour – known as Local Scour - is induced by thelocal change of cross-section geometry due to the

presence of the bridge (Graf, 1998; Richardson andDavis, 2001). Local scour usually results from the

joint effect of contraction scour, due to the flowvelocity increase associated with the reduction of

channel section, and the pier and abutment scour, dueto the (local) alteration of the flow field induced by

piers and abutments (Graf, 1998).

Table 1. Percentage of collapsed bridges over time (Imhof, 2004)

BRIDGE COLLPASE

CAUSES

All bridges

(237)

Before 1900

(35)

1900-1940

(27)

1941-1990

(117)

1991-2004

(58)

Natural hazards 40 31 37 37 50

Limited knowledge 9 14 30 7 1

Design error 5 9 0 4 5

Overloading 14 26 4 14 14

Impact 25 17 29 30 19

Human error 3 0 0 2 7Vandalism 1 3 0 0 2

Deterioration 3 0 0 6 2


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Local scour results from the removal ofmaterial from around piers, abutments, embankmentsas a consequence of the flow alteration induced by theobstruction of the flow (Richardson and Davis, 2001);local contraction scour results from the removal of

bed material across the constricted section of a bridge

crossing, where the reduced width of the cross section(in most cases) generates an increase of flow velocityand its erosive strength.

2.2. Factors influencing scour depth

Factors that may influence scour depth andscour rate vary according to the type of scour process.Geomorphic characteristic of the catchment and river

bed characteristics are the main causes of generalscour: type of vegetation, rainfall regime, riverbedsediment climatic factors determine the water andsediment transport rate at the bridge reach; channel

cross-section shape, bridge location and valley settingare riverbed characteristics that may show the bedchannel tendency towards degradation (Melville andColeman, 2000).

Man-induced structures, such as dams andreservoirs, or human activities, such as bed gravelmining are deeply responsible for general scour: Italy,for example, has reported streambed gravel mining asnumber one general scour cause, that has had anincrease since after second World War and that hasnot been properly controlled, causing exacerbated bedchannel level lowering.

Contraction scour is mainly influenced by the

magnitude of the cross-section width restriction dueto bridge piers and abutments in the channel, causingthe flow contraction at the bridge site, and by flowdebris accumulation. Floating woody debris beingtransported by the flow may accumulate at bridge

piers and abutment, partially or, in some cases, totallyclogging the bridge opening. The potential for debrisaccumulation at bridge foundations is deeply relatedto catchment characteristics and to the type ofvegetation in the catchment.

Moreover, vegetation accumulated at bridgefoundations exposes to scour a larger area around

piers and is one of the main causes of local scour

around pier foundations. The main factor in assessinglocal scour around piers is bridge geometry: theshape, type, length of the piers; bridge location inrelation to bed channel; alignment of piers with flowdirection.

Nearly 500 years ago, Leonardo da Vinci,noted that “where the river is constricted, it will haveits bed stripped bare of earth and the stones or tufawill remain uncovered by the soil” (MacCurdy,1938). This statement seems to refer to the influencethat the armouring phenomenon may have on localscour. In fact, local scour may be influenced by thearmouring phenomenon, due to the different mobility

of non-homogeneous bed soils: as scour develops intime, fine-particles at the bed surface are carried awayand, when the flow is not able to remove all sizes of

widely-graded bed sediments, the coarser materialsmay create an armour layer, protecting channel bedfrom the flow erosive action. However, if the armourlayer is not stable, when flows able to exceed themobility threshold of the coarser material occur, theunderlying riverbed material is highly exposed to

erosion and deep scour hole are expect to occur.

2.3. Clear-Water and Live-Bed Scour

Local and contraction scour depend on the balance between streambed erosion and sedimentdeposition. To this end two different scour regimeshave been defined, namely clear-water scour and live-

bed scour (Graf, 1998; Melville and Chiew, 1999;Richardson and Davis, 2001). In the former case nosediments are delivered by the river or the bedmaterial is transported in suspension through thescour hole at less than the capacity of the flow. In the

latter case an interaction exists between sedimenttransport and scour processes, due to bed material

being transported from the upstream reach into thecrossing.

Live-bed scour shows a cyclic nature: thescour hole that develops during the rising stage of aflood refills (totally or partially) during the fallingstage (Richardson and Davis, 2001). It follows that inlive-bed conditions the presence of sediments loadsleads to smaller scour depths than in clear-waterconditions.

Moreover, a different evolution in holescouring is expected: in clear water, the scour depth

increases slowly and tends to reach a stable solution;in live bed conditions, the scour depth increasesrapidly and, due to the interaction between erosionand deposition, it tends to fluctuate around anequilibrium vale (Fig. 4) (Brath and Montanari, 2000;Richardson and Davis, 2001).

In order to assess whether scour is clear wateror live-bed, a motion criteria can be used (Melvilleand Coleman, 2000), with reference to the D50, meandiameter representative of the soil particledistribution. By comparing the mean velocityupstream of the bridge, V , with the critical velocity,V c, of the D50 bed material, scour conditions will be

(Eqs. 1, 2):

Clear water 1cV

V (1)

Live-bed 1cV

V (2)

The FHWA NHI 01-001 circular (2001)indicates as typical clear water scour situations (1)coarse-bed material streams, (2) flat gradient streamduring low flows, (3) local deposits of larger bedmaterials that are larger than the biggest fraction

being transported by the flow, (4) vegetated channelsor overbank areas and (5) armoured streambeds wherethe only locations that tractive forces are adequate to


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penetrate the armour layer are at piers or/andabutments.

TIME

S C O U R D E P T H

maximum clear-water scour depth

equilibrium scour depth

clear-water scour

live-bed scour

Fig.4. Time evolution of scour depth in clear-water

and live-bed conditions

2.4. Influence of soil cohesion on scour rate

While the scour process in non-cohesivealluvial bed channels is well known and it has beenextensively investigated, little is known about theeffect that soil cohesion has on the scour patterns andscour hole evolution in time. Most of the formulationsavailable in the literature to predict local scour applynot accounting for the cohesion of the bed material:this leads to assume, in practice and by conservatism,that the maximum scour depth around bridge piers incohesive soils is equal to the maximum scour depth in

non-cohesive soils, for which several well establishedformulas are available, based on experimental modelcalibrations.

However, although maximum local scourdepth around a bridge pier can be the same incohesive soils as in non-cohesive soils, timing isdifferent (Richardson and Davis, 2001). Themagnitude of local scour is significantly influenced

by the cohesion of the bed material (Ansari et al.,2002; Brandimarte et al., 2006a; Briaud et al., 1999)that, because of the electromagnetic and electrostaticinterparticle forces, increases the scour resistance.The increased resistance offered by soil cohesion

results in a slower scour pace: thus, a more realisticestimate of time progression of the scour hole cannotneglect the effect of cohesion on local scour.

As a matter of the fact, recently, a number ofstudies have been addressed to analyze the effect ofsoil cohesion due to the important role that it plays inassessing the maximum scour depth.

Raudkivi (1991) highlighted that, unlike in thecase of non-cohesive sediments, the flow condition atwhich cohesive material get eroded is difficult to

predict as it depends upon a variety of factors such astype and percentage of clay content present, stage ofcompaction or consolidation, etc. Ansari et al. (2002)

conducted laboratory experiments on temporalvariation and equilibrium depth of pier scour underclear-water conditions in cohesive sediments. Their

results reveal that scouring in sediments having claycontent between 5% and 10% have a scour patternaround the pier that commence from the sides of the

pier, propagates then upstream along the sides andmeets at the nose of the pier, over a time that dependson the characteristic of material. Once the scour holeis initiated, the scour depth increases rapidly and

generates the deepest hole ate the nose of the pier.Briaud et al. (2002) by performing a series of 43flume test, noted, in according to the results by Ansariet al. (2002) that the scour hole in clays starts fromthe rear of the pier and that the maximum scour depthis comparable to the one in sands, although the rate atwhich scour evolves is extremely different in claysand sands.

Ariathurai and Arulanandan (1978) pointed outthat before cohesive soils can be eroded, theinterparticle bond must be broken and a critical shearstress has to be exceeded, while in the case ofcohesionless material resistance to erosion is a result

of gravity only.Wan and Fell (2004), in a study to evaluate

erosion rate of soils in embankment dams, found thatthe rate of erosion is dependent on the soil fines andclay sized content, plasticity and dispersivity;compaction water content, density and degree ofsaturation; and clay mineralogy. They conclude thatcoarse-grained, non-cohesive soils, in general, erodemore rapidly and have lower critical shear stress thanfin-grained soils.

2.5. Bridge failure mechanism

Water and sediments flowing through a bridgecan cause damage and in extreme situations failure ofthe bridge (or part of it) in a number of ways(Melville and Coleman, 2000). The most commoncause of pier failure is due to pier scour thatundermining piers and footings can cause loss ofsupport to the bridge deck. Piers and bridge deck can

be damaged by floating material, such as boulders being moved by the flow, whose impact on bridge piers and deck can destabilize supporting structures.

Floating debris accumulating at bridge pierscan generate lateral and vertical forces on bridgesand, at the same time, can clog, partially or totally,

the waterway (Fig. 5).

Fig.5. Pier failure causes: floating debris

This can dangerously result in forcing the flowto overtop the blocked bridge and washing the


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structure away. Debris accumulation is more frequentin unstable streams characterized by active bankerosion and with mild to moderate slopes. After beingmobilized, debris typically moves as individual logswhich tend to concentrate in the thalweg of the stream(Richardson and Davis, 2001). Overtopping of

bridges and roadways can also be a consequence of

sediment aggradation at the bridge site that locallyraises the stream bed level. Abutment local scour atthe toe or the face can cause a loss of support anddetermine abutment collapse.

2.6. Local pier scour processes

The presence of a bridge structure in a flowchannel inevitably involves a significant change to theflow pattern, which in turns induces changes to thestream bed elevation. Flow changes due to bridge

piers results in the formation of a scour hole at the piers, which has been recognized by several studies

(Melville and Coleman, 2000; Richardson and Davis,2001) responsible for pier undermining and thus for

pier damage or failure.The dominant feature of the flow near a pier is

the system of vortices that develops around the pierwhen unidirectional flow in erodible channel becomesthree-dimensional (Graf, 1998; Melville andColeman, 2000; Shen et al., 1969). Depending on

bridge geometry and flow conditions, the system ofvortices can be composed by all, any or none of threeindividual basic systems acting at the pier (Fig. 6): a)the horse-vortex system at the base of the pier; b) thewake-vortex system downstream of the pier; c) the

surface roller ahead of the pier.

Fig.6. Sketch of the system of vortices at a bridge pier

The horseshoe-vortex (Fig. 6) is due to thevertical component of a downward flow, namely fromhigh to low velocities, observed in front of the pier asa result of the stagnating pressure gradient, as theflow approaches the pier (Raudkvi, 1991). Althoughthe downward flow will be laterally diverted by a

pressure gradient around the pier, it is generally

agreed upon that it is the vertical component of theflow the one responsible for removing bed material(Graf, 1998). Due to the stagnation pressure, the

water surface, in upstream of the pier, increasesresulting in a surface roller.

If the pressure field is sufficiently strong, itinduces a three-dimensional separation of the

boundary layer and the horse-vortex system formsitself at the base of the pier (Graf, 1998; Shen et al.,1969). The downward flow impinging on the bed acts

like a vertical jet in eroding a groove immediatelyadjacent to the front of the pier (Melville andColeman, 2000). Contrary to the case of the horse-vortex system, the wake-vortex system is generated

by the pier itself: it is due to the rolling up of unstableshear layers at the surface of the pier (Shen et al.,1969). The wake vortices arise from either side of the

pier at the separation line and are transporteddownstream by the flow.

Shen et al. (1969) noticed that this vortexsystem is stable for low Reynolds numbers (3 to 5


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5.0

11.1

b

y

b

z (3)

where: z(m) is the final scour depth; b is the pierdimension and y is the water depth.

Among formulations that apply in clear-water

conditions, the one proposed by Shen et al. (1969) has been for years the most used one (Eq. 4):

619.0

00022.0

Vb z (4)

Being υ the cinematic viscosity of water and Vthe mean flow velocity. This formulation was one ofthe first empirically derived attempt to evaluate finalscour depth at piers and most of the next formulationsthat have been proposed in the literature in thefollowing decades, have been derived from Shen’sdata.

The equation by Hancu (1971) involves thedependence of scour depth from the critical velocityV c, that establishes the threshold condition for bedmaterial being removed. In Eq. 5, g is the accelerationof gravity:

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1242.2

gb

V

V

V d z c

c

(5)

In 1988 Melville and Sutherland developed amodel that evaluates scour depth by as a function ofthe pier dimension and correction factors that account

for flow characteristics and pier geometry (Eq. 6).

b K K K K K z d s y I (6)

where: K I , K y and K d are function of, respectively, theV/Vc ratio, the upstream flow depth-pier size ratio, thesediment size; K s and K δ depend on the pier shape andthe pier alignment.

Ansari and Qadar (1994) proposed anenvelope equation that fitted more than 100 fieldmeasurements of pier scour depth from different case

studies in several countries (Eq. 22).

0.386.0 b z mb 2.2

4.06.3 b z mb 2.2 (22)

where: the only parameter influencing scour depth isthe pier dimension.

The equation proposed by Richardson andDavis (1995), (Eq. 23) known as CSU (ColoradoState University) equation, is the one recommendedin the Hydraulic Engineering Circular, HEC-18, and itis widely used in the United States.

43.0

65.0

2 m A f s yF y

b K K K K z

(23)

where: F m is the Froude number of the upstream flowand K f and K A are corrective factor accounting for bedcondition and armouring effect by bed material. Thisequation was obtained plotting laboratory data forcircular piers.

In 1997 Melville modified the relation byMelville and Sutherland (1988) to include differentcorrective factors to express the relationship between

scour depth and pier geometry and cinematiccharacteristics of the flow.

Table 2. Selection of empirical equations to evaluate local pier scour

Authors Equation Authors Formulation

Laursen (1958)5.0

b

y 1.11b z

(7) Jainb(1981)

25.0

rc

3.0

F b

y 1.84b z

(15)

Larras (1963)0.75

s b K K 1.05 z (8) Chitale (1988) b5.2 z (16)

Breusers (1965) 1.4b z (9) Melville andSutherland (1988) K K K K bK z sd y I (17)

Shen et al.(1969)

0.619Vb

0.000223 z

(10) Breusers and Raudkivi(1991) K K K K bK 3.2 z sd y (18)

Coleman (1971)

0.9

b

V 0.6

2gz

V

(11) Richardson and Davis

(1995)43.0

r

35.0

A f s F b

y K K K K 2b z

(19)

Hancu (1971)

3 / 12

c

c gb

V 1

V

V 2b42.2 z

(12) Ansari and Qadar

(1994) 40

3

63

860

.

p

p

b. z

b. z

m.b

m.b

p

p

22

22

(20)

Neill (1973) b K z s (13) Melville (1997) K K K K K z sd I yb (21)

Jain and Fischer(1980)

25.0

rcr

5.0

F F b

y 1.86b z

(14)


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However, due to the lack of field data and tothe complexity of the scour phenomenon, theseformulations have several limitations: a) they arederived for simple solid pier foundations with limitedattention for scour depth developing in the case of

pile groups, pile groups and pile caps (Salim and

Jones, 1996); b) the laboratory representations of thestream reach involving bridge scour is often timesrealized by means of straight, typically rectangularlaboratory flumes; c) these formulations assumesteady flow conditions; d) the bed material is assumedto be non cohesive.

The application of these conservativeformulations leads to an overestimation of the scourhole (Melville and Coleman, 2000; Richardson andDavis, 2001). This implies an overestimation of

bridge foundations that results in an economic wasteduring bridge designing. As shown in Table 2, someof these equations have the velocity as a variable,

either as mean flow velocity or as Froude number;some of them, however, are independent from flowvelocity. As shown in the study by Jones, thesecommonly used equations may provide, for the samecase study, really different scour values, due to thevariability of parameters involved in these equations.This consideration should suggest bridge engineers tocarefully select the methods to perform, whenevaluating bridge scour vulnerability, according to thecase study characteristics, in order to apply severaldifferent methods to be able to critically comparescour depth values obtained by performing theseequations.

In order to support them in their decisionmaking, the scientific literature has providedengineers a myriad of empirical formulations forestimating scour depth at bridge crossings. However,these formulations, derived in the laboratories,interpret the scour process under several assumptionsthat might limit their application. In fact, most of theformulations that are used in common practice referto clear-water conditions, cohesionless bed materials,and steady flow conditions. These assumptions leadto an overestimation of the scour depth that, in thecourse of bridge design, may lead to unnecessary,non-economical, deep foundations (Richardson and

Davis, 2001).The hypothesis of clear-water conditions, used

because of the difficulty of interpreting andestimating the bed material being transported by theflow, does not take into account the effect of thecyclic material detachment and replacement. Indeed,in live-bed conditions, an equilibrium scour depthvalue is reached in a shorter time period and leads to ascour hole less deep that the one produced in clear-water conditions (Richardson and Davis, 2001).

3.2. Numerical methods

Although easy to apply and quite widely usedin engineering practice, the empirically derivedequations for the estimate of scour depth do have, as

mentioned above, intrinsic limitations. Furthermore,they do not account for the actual, complex, three-dimensional sediment removal process taking place at

piers.Over the past two decades, some interesting

studies attempted to reproduce the flow patterns

around bridge piers by means of detailed 3Drepresentation of the turbulent horseshoe vortexsystem that triggers scour at bridge piers. Olsen andMelaaen (1993) and Olsen and Kjellesvig (1998) usedfinite-volume method to solve Reynolds-averaged

Navier-Stokes equations around a cylindrical pier ona non cohesive bed in clear water conditions. Theycalibrated their model based on the scour observationsmeasured in a physical model. Richardson andPanchang (1998) performed fully 3D numericalsimulations to reproduce the flow pattern at acylindrical pier and compared the outputs of theirstudy with laboratory measurements. Although the

satisfactory agreement between the two approaches,authors concluded that the discrepancies theyobserved in the results of the two methods can be dueto the choices in numerical model parameters. Tsenget al. (2000) used a finite volume method to analyze

by means of a numerical model, the flow field aroundsquare and circular piers and compared, with goodagreement, their results with the experimental studycarried out by Dargahi (1990).

The geometry of the pier does not seem tohave a significant impact on the flow pattern, but itdoes influence the position of the horseshoe vortexwhich, in the case of the circular pier is closer to the

upstream side of the pier. Salaheldin et al. (2000) runthree-dimensional numerical model to simulate theseparated turbulent flow around circular piers in clearwater conditions. They performed differentturbulence models and compared their results withseveral sets of experimental data available in theliterature and concluded that a robust 3Dhydrodynamic model can capture the scour initiation

process around piers having different size and shape.Various studies agreed on the capability of the

unsteady Reynolds-averaged Navier-Stokes models tosimulate turbulence at bridge piers of differentgeometries. However, as pointed out by

Khosronejad et al. (2012) turbulence modelsusually adopted for closing the Reynolds-averaged

Navier-Stokes equations tend to under-represent theeffect of the important features that participate in theinitiation of the turbulent horseshoe vortex system,since they tend to overpredict the magnitude of theeddy viscosity at the pier foundation.

To smooth the limitations of this approach, anumber of researchers have tried to integrate unsteadyReynolds-averaged Navier-Stokes and large eddysimulations or detached -eddy simulations approachesand strengthened the understanding of the complexscour initiation phenomenon by comparing their

numerical results to experimental works (Kirkil et al.,2009; Paik et al., 2010).


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However, although accurate in reproducing thedynamics of the vortex system at the pier, theapplication of such models in the commonengineering practice to evaluate the expected scourdepth at the bridge pier is difficult due to thecomputational resources needed (Khosronejad et al.,2012).

3.3. Data driven methods

To overcome the limitations given byempirically derived formulae to estimate pier scourdepth, without having to carry out time consuming,complex 3D numerical modeling, recently, thescientific literature has devoted several efforts intoexploring the possibility to use data driventechniques, where no a priori relationship betweenknown parameters and observed values has to behypothesised and no knowledge of the underlying

process is needed. In particular, many studies using

the so called Artificial Neural Networks (ANN) haveshown to be promising in predicting bridge scour(Bateni et al., 2007b; Firat and Gungor, 2009; Jeng etal., 2005; Lee et al., 2007; Toth and Brandimarte,2011). ANN have been widely applied in the lastdecade to a variety of problems, including civilengineering applications (an introduction to artificialneural networks and examples of their application incivil engineering can be found in Flood and Kartam,1994a, 1994b), mainly due to their capability toflexibly reproduce also highly non-linearrelationships.

Neural networks distribute computations to

relatively simple processing units called neurons,grouped in layers and densely interconnected (Fig. 7).Three different layer types can be distinguished: inputlayer, connecting the input information (and notcarrying out any computation), one or more hiddenlayers, acting as intermediate computational layers

between input and output, and an output layer, producing the final output, the estimated equilibriumscour depth.

Input layer Hidden layer

Output layer

Fig.7. Three-layer architecture of an artificialneural network

In correspondence of each computational node

(Fig. 8), each entering value (IJi) is multiplied by aconnection weight (wij). Such products are then allsummed with a neuron-specific parameter, called bias

(bj), used to scale the sum of products into a usefulrange. The computational node finally applies a non-linear activation function (f) to the above sum

producing the node output (OJ). Neural networks aretrained (i.e. calibrated) with a set of observed inputand output data pairs (called target to be distinguishedfrom the network final output), which is processed

repeatedly, changing the values of the parametersuntil they converge to values such that each inputvector produces output values as close as possible tothe desired target vectors.

IJ1

IJ2

IJ3

IJ4

IJ5

w1j

w2j

w3j

w4j

w5j

b j

NIJ

i

jiij b IJ w1

NIJ

i

jiij b IJ w f OJ 1

Fig.8. Information computation at one single node

As mentioned above, the application of theANN to the estimate local scour at bridge piers has

been recently addressed in many studies, takingadvantage of their capability to flexibly reproduce thehighly non-linear nature of the relationship betweeninput and output variables, also when suchrelationship is not explicitly known a priori.

In a very popular paper, Bateni et al. (2007)investigated the performance of artificial neuralnetworks and adaptive neuro-fuzzy inference systems

(ANFIS) in predicting the equilibrium and time-dependent scour depth. The authors built twodifferent ANN models on a large dataset of laboratorydata: multi-layer perception using back-propagationalgorithm (MLP/BP) and radial basis usingorthogonal least-squares algorithm (RBF/OLS). Theyselected 5 input variables, representing the scour

phenomenon and affecting the equilibrium scourdepth: flow depth, mean velocity, critical flowvelocity, mean grain diameter and pier diameter. Theyconcluded that MLP/BP models performed better thanRBF/OLS and ANFIS models and over performedclassical empirical approaches and, via a sensitivity

analysis, they found out that the dimension of pierdiameter is the most affecting input variable onequilibrium scour depth.

Firat and Gungor (2009) investigated thecapability of ANN in estimating local pier scour bymeans of two different techniques, the GeneralizedRegression Neural Networks (GRNN) and FeedForward Neural Networks (FFNN) applied to 165data records collected from the literature. Theyconcluded that the GRNN performs better than theFFNN in predicting the equilibrium scour depth and,as already pointed out by Bateni et al. (2007), the pierdimension and mean grain size input variables are the

most influential variables on scour depth.However, many of these applications, made

use of limited datasets, which represent of the main


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limitations of the ANN, and do not differentiate between scour processes occurring in clear-water orlive-bed conditions, which, as described above, highlyaffect the evolution of the scour hole. Recently, Tothand Brandimarte (2011) collected an extensive fieldand laboratory database of observed pier scour andapplied ANN models for the prediction of scour depth

at bridge piers, taking explicitly into account for thetransport mode conditions. Observed scour recordscollected from different sources, and relative to bothlaboratory experiments and field campaigns, wereused to create different training subsets, with anincreasing degree of specialization: modelsdistinguishing field and laboratory data, clear-waterand live-bed conditions were applied to investigatethe capability to predict the equilibrium (or quasi-equilibrium) scour depth over an external validationdata set. The performances obtained through theimplementation of the Artificial Neural Networks arecompared to those obtained by applying eight of the

most widely used literature formulae to the sameexternal validation data.

3.4. Uncertainty

Over the past two decades, there has been anincreasing interest in estimating uncertainty inhydraulic and hydrological studies, which has beenrecognized to be important in the communication ofmodel results with end users (Beven and Freer, 2001;Merwade et al., 2008).

Uncertainty in the estimation of bridge pierscour is caused by many sources of error that

propagate through the model therefore affecting itsoutput. The main sources of uncertainty can beclassified as: i) observation uncertainty, which is theapproximation in the observed hydraulic variablesused as input of the bridge pier estimation methods(e.g. flow regime, topography); ii) parameteruncertainty, which is induced by imperfect

parameterization of these methods (e.g. shapes,materials); iii) structural uncertainty, which isoriginated by the inability of the estimation methodsto perfectly schematize the physical processesinvolved in bridge pier scour.

An example of observation uncertainty is the

inaccuracy that may occur in measuring field scourmeasurement because it is unknown if the river bedhas reached an equilibrium state at the time ofdischarge and scour measurements (Lee and Sturm,2009).

Johnson and Ayyub (1996) dealt with parameter uncertainty and proposed the use of fuzzyregression for the analysis of the uncertainty in bridgescour predictions. In this approach, the regressioncoefficients are fuzzy parameters and the output, i.e.the predicted scour depth, is also a fuzzy number.

Lastly, structural uncertainty is typically veryhigh because of the complexity of all the processesthat come into play (Larsen et al., 2011) and thereforeour capability to predict the time development ofscour remains poor (Ettema et al., 2011). This is why

the standard approach is to focus on the potentialmaximum scour depth at a pier site, withoutaddressing the complex dynamic of bridge scour(Ettema et al., 2011). Also, this uncertainty istypically addressed by implementing a conservativeapproach and using safety factors. In fact, mostexisting equations are generally conservative and tend

to overestimate the scour depth (Deng and Cai, 2010).However, this approach might lead to veryconservative and often unreliable estimations (Ettemaet al., 2011). Uncertainty can also be differentiated asaleatory uncertainty, which is related to naturalvariability and randomness, and epistemicuncertainty, which is due to our incompleteknowledge (Apel et al., 2004). A differentclassification is proposed by Johnson and Ayyub(1996), who also included additional sources ofambiguity due to conflicts in information as well ashuman and organizational errors.

In analyzing the effect of riverbed sediment

cohesion on pier and contraction scour depth,Brandimarte at al. (2006a; 2006b) developed a new

probabilistic framework to evaluate risk associatedwith bridge scour in cohesive soils. The uncertaintyinherent to hydrological and climatological dynamicscontrolling the regime of river flow suggest using astochastic approach to determine the risk associatedwith different design values of scour depth.

Brandimarte et al. (2006a) coupled a stochasticmodel, commonly used in hydrological modeling,with a scour model, developed by Briaud et al. (2001)which determines the progression of pier scourthroughout the bridge life in cohesive soils: 1) the

streamflow sequence is modeled as a stochastic process; 2) a Monte Carlo procedure is applied, whichsamples from that process different replicates of thehydrologic series of the same length as the expectedlifetime of the bridge; 3) for each streamflowsequence, the scour model generates a scour depthhistory; and 4) the scour depth, z, at the end of the

bridge life will be determined. Thus, the scour depthis treated as a random variable and different replicatesof scour depth will be estimated through the MonteCarlo random sampling procedure. The statistics of zare then performed to determine the risk of failureassociated with different choices of the scour depth

design values.

4. Measurements

Bridge pier scouring consists of negativevariations in river bed topography in the proximity of

piers and aprons under bridges. They happenrepeatedly in time, being excavated and filled inseveral occasions during the life of a structure. Theexcavation and in-filling process happens during highflows and their receding curve, so in this perspectivescouring and infilling are two aspects of the same

process. Depending on the local conditions thescouring/infilling can be superficial, involving only athin layer of sediments (of varying grain size) or canalso cut deep through the whole sediment pack and


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bedrock (especially if made up of over-consolidatedclays, or sandstones, or similarly soft rocks) and

being refilled.Therefore the measurement of real-time bridge

pier scouring (i.e. bottom profile) needs to happenduring the event of maximum excavation (flood)while the measurement of subsequent infilling (i.e.

bottom plus sub-bottom profile) can also be performed after the event that causes it. An advantageof measuring the sub-bottom profile is that ithighlights the history of scouring, providing usefulinformation for the modelling and management(Forde et al.; 1999Millard et al., 1998).

Within the several available methods tomeasure scour-infill it is possible to define two maincategories: direct and indirect (or geophysical)methods. Another subdivision can be drawn betweenthose providing 2D and those allowing for 3D(volumetric) reconstruction of the scouring history.Table 3 illustrates the various methods subdivided

into direct and indirect observation.Among the direct methods the steel sliding rod

and steel ring are the simplest, mechanical ones,allowing for the determination of the depth of thescour when the scouring happens; they are based on

pvc pipe lowered to river bed at time 0 and with a rodin it. When the river bed is scoured at time 1 the rodwill lower and the difference in depth can bemeasured against a reference.

Discharge survey methods consist oftraditional current-meter attached to a crane andlowered down to the river bed and during flood times(Bohemler and Olimpio, 2000). This allows for both

bottom profiling in discrete locations and depth-integrated discharge measurement. Diver's inspectionof scouring and pier status is a risky method andshould be discouraged especially because it needs to

be done during flood times to capture the maximumscouring and also because it cannot investigate theinfilled scours (Millard et al., 1998).

Drilling the river bed is practiced in the UK asa standard technique (Forde et al., 1999) and has theadvantage of providing continuous logs of thesediments and, if the sample is undisturbed, can also

be a useful way to get a quantitative history ofscouring. The location of drilling needs to be properly

assessed before its execution. An array of geophysicalmethods allows for the determination of bottom andsub-bottom profiles, and liquid and solid discharge.They all fall into the geophysical family and needadditional calibration to be properly interpreted. Themost common ones use electromagnetic impulses in

the window of radar wave-lengths (at frequencies of50 -300 MHz typically for geotechnical studies,Millard et al., 1998) or acoustic waves (ADV andADCP, at frequencies from few hundred to severalthousands of KHz) or elastic waves (seismicmethods). All of them require a strong difference inwave conductivity between the water and the

sediments to be effective. The electromagnetic onesare restricted by high values of water salinity thatabsorbs most of the signal.

Among the many available the GroundPenetrating Radar (GPR) and Continuous SeismicReflection Profiling (CSRP) offer the most reliablemethods of surveying both the water depth and thesub-bottom profiles, including also information on thetype of infilling sediments (Bohemler and Olimpio,2000; Deng and Cai, 2010; Forde et al., 1999; Inchanet al., 2004; Millard et al., 1998; Placzek and Haeni,2007). Furthermore -if surveyed along several sets of

parallel lines- they can be used to derive a 3D picture

of the river bed and its subprofile. Also geophysicalmethods have the advantage of not interfering

physically with the scouring process itself.The fixed sensor methods incur many

limitations, the main one being twofold: thegeometrical layout of pier/sensor geometry (and theirexposure to vandalism and natural hazards (Bohemlerand Olimpio, 2000). The sensors are usually attachedlaterally or frontally to the pier and the pier foot can

be armoured or having an apron of protection. Thislayout limits very much the capture of the scouring bythe sensors or it implies protruding sensors attachedto the pier that become more exposed to floating

debris during high flows. For this reason mobiledevices are preferable if armouring of the pier feet arein place.

5. Conclusions

Scour at hydraulic structures is one of the mainissues engineers have to face at various stages of thestructure life: during design, operation andmaintenance. Scour at bridge piers is the main causefor bridge failure and might represent a potentialthreat to the civil population.

The scientific community has made enormous

advances in understanding the scour processdynamics and has explored different approaches toestimate the maximum expected scour depth at bridge

piers. These advances provide tools for supportingengineers in the design phase of adequate bridgefoundations.

Table 3. Direct and indirect pier scour observation methods

Direct /

Indirect

Fixed/Mobie

Device Method

Feature Measured

(dis.=discrete;

cont.=continuous)

During/

post

event

1D/2D/

3D Pros Limitations

References

DirectMobile (boat) Steel

(sliding) rod(manned)

Bottom (dis.) Post 1D Quick, cheap,easy, sturdy (noelectronicsinvolved)

Only for wadablerivers

Forde et al.,1999; Bohemlerand Olimpio,2000; Deng and


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Cai, 2010;Lu et al., 2008

FixedSteel slidingring

Bottom (dis.)During& Post

1D

Quick, cheap,sturdy (noelectronicsinvolved)

Can be appliedonly on pierswithout aprons orarmouring.

Bohemler andOlimpio, 2000;Lu et al., 2008

Mobile (boat) Diving Bottom (dis./cont.) Post

Can survey severalfeatures at a timeand also addobservations byexpert personnel

Semi-quantitative;Dangerous; Needs specialized personnel

Forde et al.,1999; Bohemlerand Olimpio,2000

Mobile (car)

Dischargesurvey(cranemountedcurrentmeter)

Bottom & Discharge(dis.)

During& Post

2D

Provides twomeasures at atime; relativelycheap;

Dangerous for thedivers, expensive,needs clearwaters

Bohemler andOlimpio, 2000

Mobile(manned)

Topographicsurvey

Bottom (dis.) Post 2DForde et al.,1999

Mobile(floating platform. bridge)

Drilling (inthe river bed)

Bottom & Sub-Bottom (dis.)

Post

1D &2D(fencediagram)

Sub-bottomvertical profiles,logs of fillingmaterials

Needs a largefloating platform,expensive, noteasy to repeat intime

Fixed (bridge piers)

ADV During& Post

3DHigh-resolution3D velocitymeasurements.

Flow disturbancedue to pierdiameter.

Sarker, 1998;Lee andGotvald, 2004

Fixed (bridge piers)

H-ADCP

Bottom, Discharge& Suspendedsedimentconcentration (cont.)

During& Post

2DHorizontal profiles;

Needs a mounton the river bank; bridge piers cancreate shadows ofnon-visibility

Muste et al.,2012

Mobile(boat/floating platform)

ADCP

Bottom, Discharge& Suspendedsedimentconcentration (cont.)

Post 2DMeasures flow &sedimentconcentration

Limited withsedimentconcentration > ;expensive

Deng and Cai,2010;Lu et al., 2008

Fixed /Mobile

Acoustic /Sonar

Bottom (dis./cont.)During& Post

2D

Forde et al.,1999; De Falcoand Mele, 2002;Lu et al., 2008

Fixed /Mobile

Fathometer/Echosounder

Bottom & Sub- bottom (dis./cont.)

During& Post

2DEasy and quick touse

Bohemler andOlimpio, 2000;Millard et al.,1998; Lee andGotvald, 2004;Placzek andHaeni, 2007

Mobile /

Fixed

GroundPenetratingRadar - GPR

Bottom & Sub-

bottom (cont.)Post

2D &

3D

Assessment of bottom & sub- bottom geometryand infillingmaterial. Canwork with highload of suspendedsediments andreaches down.Water depths up to10 m

Needs highlyskilled personnelfor proper surveyandinterpretation.Improved resultsif calibrated withdrilling orgeological logs,and if strongdielectricdifference between river bedand sediment. Not usable insalty water

Forde et al.,1999; Bohemlerand Olimpio,2000; Millard etal., 1998; Dengand Cai, 2010;Placzek andHaeni, 2007;Park et al.,2004;Lu et al., 2008

Indirect

Mobile

Shallowseismic/ContinuousSeismicReflection

Profiling

Sub-bottom (cont.) Post2D &3D

Assessment ofsub-bottomgeometry andinfilling material.Can reach downup to the bedrock

and further into it.Provides 2D profiles.

Needs highlyskilled personnelfor proper surveyandinterpretation.Improved resultsif calibrated withdrilling or

geological logs. Not usable inshallow waters

Forde et al.,1999; Placzekand Haeni, 2007


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The numerous empirically derived available to predict pier scour are easy to apply and are stillwidely applied in the engineering practice, but theyseem to over or under estimate the scour depth whenthey are applied outside the range of applicability forwhich they are derived in the laboratory experiments.

Data driven approaches can provide a validalternative to the empirically derived formulae, but awide dataset of data is needed for a proper trainingand validation of the fitting relationships; moreover,neural networks, although over performing whencompared to the empirical equations, might fail in beexported outside the range of training and validation.

Detailed numerical modeling of the complexthree dimensional scour processes taking place at the

pier are now available and have proven to be able tocapture the horseshoe vortex dynamics that initiatethe sediment removal.

Nevertheless, the implementation and

applicability of such complex models might belimited due to the computational resources needed tocarry out a fully three dimensional analysis.

This paper presented, analyzed and discussedthe three main topics relevant in bridge pier scouring:1) the physical processes taking place at the pier-foundation level; 2) the different approaches availablein the literature for estimating scour depth at piers and3) the most used methods for pier scour observations.Furthermore, this review addressed the complex issueof quantifying the uncertainty associated to the pierscour estimate, caused by the many sources of errorthat propagate through the models: observation

uncertainty, parameter uncertainty, structuraluncertainty.

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